Paper short abstract:

We examine how the Covid-19 restrictions impacted well-being of residents in Kolkata, the third largest Indian city, based on an unique survey conducted during the lockdown between May and June 2020. There are several features within our data which allows for interesting analysis. Preliminary analysis has shown that the individual life-satisfaction was worse in the red zones.

Paper long abstract:

Context: The Covid-19 pandemic imposed unprecedented lockdowns across cities and countries. It lead to reduction of economic activity and substantial impact on individual physical and mental health ( Banerjee et al., 2022). While significant research is still being undertaken on the impact of Covid-19, there is little evidence, particularly for developing countries, on the impact of the Covid-19 related restrictions impacted individuals health and economic outcomes.

Aims and Objective: In this paper, we examine how the Covid-19 restrictions impacted the physical, mental and economic well-being of residents in Kolkata, the third largest Indian city with a population of 15 million, based on a survey we conducted between May and June 2020. We investigate the impact of the lockdowns on individual's well-being through a varied set of outcomes such as income, working hours, overall life satisfaction. Given the strong evidence of anxiety due to lockdowns in India (Banerjee et al. 2022) we also examine whether during the lockdown they were able to access their savings and insurance, whether they suffered any losses. Finally, for a smaller part of the sample, we also measure their blood-cortisol level as an indicator of stress. Our aim is to empirically demonstrate how all these individual outcomes were impacted by the Covid-19 lockdown in Kolkata, where in particular the city was divided in to Red, Orange and Green zones.

Data: We collected a unique data set based on surveying individuals coming for health tests at a diagnostic lab (Genu Path Labs) in Kolkata. This is a large diagnostic lab with collection centres all across Kolkata. Most of our sample came from the main lab at Salt lake in Kolkata. The survey was mainly done through over telephone, and in some contexts through survey monkey. We were able to survey 332 individuals, out of which 33 were from Red zones, 46 from Orange zones and 236 from Green zones. There were 151 females and 181 males in our sample. The average age was 52, with the minimum and maximum age being 19 and 90 respectively.

While this does not seem like a random sample, we believe that this still allows us access to individuals from varied spheres of life. During our survey period the lock down has just begun to ease and there were still no possibility of conducting city wide surveys. Most of the studies examining the health and well-being of individuals in India at that time has used online surveys (Banerjee et al. 2022). However, we wanted to move away from online surveys to capture those who may not access the internets, which includes not only the lower socio-economic groups but also senior citizens. A valid criticism may be that we are oversampling from individuals with health issues, however, in our analysis we will control for the main health issues that individuals may have.

Identification and Method: There are several features within our data which allows for interesting analysis. First, part of our data is individuals recalling their pre-covid information on income, working hours, life-satisfaction. Given that our survey was conducted within a couple of months of lockdown, it is not unreasonable to expect that individuals will have a clearer idea of the current situation vis-à-vis pre-lockdown situation. Our recall questions were not asking for detailed information about the individuals living standards, instead they were asking the broad questions about health, income and overall welfare. For instance, with income, we have asked individuals to fill in the broad income slabs, they were in rather than a precise income information. Hence, we believe that individuals have reported those outcome variables honestly and consistently. Thus, we use this recall information to understand the difference in the outcomes between the pre-lockdown and during lockdown periods. The second aspect is about the different zones in Kolkata. The different zones had different restrictions leading to different impact on individuals residing on those zones. These treatment and control zones were based on postcodes and could be considered as contiguous. This allows us to not to worry about fixed effects that typically would be the case in most analysis. We therefore can deploy as simple regression based difference analysis to understand the impact of the zones on individual outcomes.

Analysis and Conclusion: Preliminary analysis has shown that the individual life-satisfaction was worse in the red zones. We also find stress parameters such as cortisol, higher in the Red zone compared to other zones. We want to think through this analysis more carefully and want to establish a causal link between covid related restrictions and individual wellbeing.